With the advent of PCR-based STR typing systems, mixed samples can be separated into their individual DNA profiles. Quantitative peak information can help in this analysis. However, despite such advances, forensic mixture analysis still remains a laborious art, with the high cost and effort often precluding timely reporting.
This invention describes a new automated approach to resolving forensic DNA mixtures. This “linear mixture analysis” (LMA) is a straightforward mathematical approach that can integrate all the quantitative PCR data into a single rapid computation. LMA has application to diverse mixture problems. As demonstrated herein on laboratory STR data, LMA can assess the quality and utility of its solutions. Such rapid and robust methods for computer-based analysis of DNA mixtures are helpful in reducing crime.
In forensic science, DNA samples are often derived from more than one individual. In such cases, key objectives include elucidating or confirming a mixed DNA sample's component DNA profiles, and determining the mixture ratios. Current manual qualitative peak analysis of mixed DNA samples is slow, tedious, and expensive. These difficulties can generate considerable delay in the casework analysis of forensic DNA mixtures, underscored by the current USA backlog comprised of over 100,000 unanalyzed rape kits.
Under appropriate data generation conditions, STR peak data can be quantitatively analyzed. Such quantitative approaches have spawned heuristic and computer-based methods that can potentially resolve these complex data. These prior art statistical computer programs are limited in that they typically analyze each STR locus separately, and may require human intervention when combining the locus results into a complete nonoptimized solution (Clayton T M, Whitaker J P, Sparkes R, Gill P. Analysis and interpretation of mixed forensic stains using DNA STR profiling. Forensic Sci. Int. 1998; 91:55-70; Evett I W, Gill P, Lambert J A. Taking account of peak areas when interpreting mixed DNA profiles. J. Forensic Sci. 1998; 43(1):62-69; Gill P, Sparkes R, Pinchin R, Clayton T M, Whitaker J P, Buckleton J. Interpreting simple STR mixtures using allele peak area. Forensic Sci. Int. 1998; 91:41-53), incorporated by reference.
The present invention includes a quantitative analysis method that describes the mixture problem as a linear matrix equation. One name for this novel DNA analysis approach is “Linear Mixture Analysis,” or “LMA”. Unlike previous methods, the mathematical LMA model uses STR data from all the loci simultaneously for greater robustness. The linear mathematics permits rapid computer calculation, and provides a framework for statistical analysis. An associated error analysis can measure the quality of the overall solution, as well as the utility of each contributing locus.
This specification details the generation of linear mixture data, novel methods of linear mixture analysis, a nonobvious mixture deconvolution technology for determining unknown mixture components, an associated error analysis, the computation of probability distributions, a set of statistical tests, useful bootstrap simulation methods, user interfaces and data visualization for communicating results, utility in forensic applications, and useful extensions of linear mixture analysis.